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Bayesian Phylogenetics with BEAUti and the BEAST 1.7

Alexei J. Drummond; Marc A. Suchard; Dong Xie; Andrew Rambaut · Molecular Biology and Evolution · 2012

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Computational evolutionary biology, statistical phylogenetics and coalescent-based population genetics are becoming increasingly central to the analysis and understanding of molecular sequence data. We present the Bayesian Evolutionary Analysis by Sampling Trees (BEAST) software package version 1.7, which implements a family of Markov chain Monte Carlo (MCMC) algorithms for Bayesian phylogenetic inference, divergence time dating, coalescent analysis, phylogeography and related molecular evolutionary analyses. This package includes an enhanced graphical user interface program called Bayesian Evolutionary Analysis Utility (BEAUti) that enables access to advanced models for molecular sequence and phenotypic trait evolution that were previously available to developers only. The package also provides new tools for visualizing and summarizing multispecies coalescent and phylogeographic analyses. BEAUti and BEAST 1.7 are open source under the GNU lesser general public license and available at http://beast-mcmc.googlecode.com and http://beast.bio.ed.ac.uk.

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APA 7

Drummond, A. J, Suchard, M. A, Xie, D, & Rambaut, A. (2012). Bayesian Phylogenetics with BEAUti and the BEAST 1.7. https://doi.org/10.1093/molbev/mss075

MLA

Drummond, Alexei J, et al. "Bayesian Phylogenetics with BEAUti and the BEAST 1.7." 2012. https://doi.org/10.1093/molbev/mss075.

Chicago

Drummond, Alexei J, Marc A. Suchard, Dong Xie, and Andrew Rambaut. 2012. "Bayesian Phylogenetics with BEAUti and the BEAST 1.7.". https://doi.org/10.1093/molbev/mss075.

Harvard

Drummond, A. J. et al. 2012, Bayesian Phylogenetics with BEAUti and the BEAST 1.7, Molecular Biology and Evolution, available at: https://doi.org/10.1093/molbev/mss075 [Accessed 7 Aug. 2026].

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Title
Bayesian Phylogenetics with BEAUti and the BEAST 1.7
Author / contributors
Alexei J. Drummond; Marc A. Suchard; Dong Xie; Andrew Rambaut
Publisher
Molecular Biology and Evolution
Publication year
2012
Language
English

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